On Succinct Groundings of HTN Planning Problems
Gregor Behnke, Daniel Höller, Alexander Schmid, Pascal Bercher, Susanne Biundo
Abstract
Both search-based and translation-based planning systems usually operate on grounded representations of the problem. Planning models, however, are commonly defined using lifted description languages. Thus, planning systems usually generate a grounded representation of the lifted model as a preprocessing step. For HTN planning models, only one method to ground lifted models has been published so far. In this paper we present a new approach for grounding HTN planning problems that produces smaller groundings in a shorter timespan than the previously published method.
Topics & Concepts
PreprocessorComputer scienceRepresentation (politics)Operations researchArtificial intelligenceManagement scienceEngineeringPolitical sciencePoliticsLawAI-based Problem Solving and PlanningSemantic Web and OntologiesNatural Language Processing Techniques